Overview

Brought to you by YData

Dataset statistics

Number of variables18
Number of observations785916
Missing cells1153445
Missing cells (%)8.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory498.0 MiB
Average record size in memory664.5 B

Variable types

Numeric8
DateTime1
Categorical2
Boolean3
URL2
Text2

Alerts

isEdNeed has constant value "True" Constant
edInput is highly overall correlated with editor and 1 other fieldsHigh correlation
editor is highly overall correlated with edInput and 1 other fieldsHigh correlation
engages is highly overall correlated with likes and 1 other fieldsHigh correlation
isApproved is highly overall correlated with edInput and 1 other fieldsHigh correlation
isRT is highly overall correlated with rtUsIDHigh correlation
likes is highly overall correlated with engages and 1 other fieldsHigh correlation
retweets is highly overall correlated with engages and 1 other fieldsHigh correlation
rtUsID is highly overall correlated with isRT and 1 other fieldsHigh correlation
usFlwrs is highly overall correlated with rtUsID and 1 other fieldsHigh correlation
usID is highly overall correlated with usFlwrsHigh correlation
photoUrl has 508020 (64.6%) missing values Missing
videoUrl has 645425 (82.1%) missing values Missing
engages is highly skewed (γ1 = 62.99060734) Skewed
likes is highly skewed (γ1 = 60.77687391) Skewed
retweets is highly skewed (γ1 = 101.2684199) Skewed
retweets has 26349 (3.4%) zeros Zeros

Reproduction

Analysis started2025-03-15 06:36:23.451101
Analysis finished2025-03-15 06:37:05.110129
Duration41.66 seconds
Software versionydata-profiling vv4.14.0
Download configurationconfig.json

Variables

tweetID
Real number (ℝ)

Distinct744731
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1152126 × 1018
Minimum53545
Maximum1.1541792 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2025-03-14T23:37:05.154390image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum53545
5-th percentile1.0762031 × 1018
Q11.0957907 × 1018
median1.1164652 × 1018
Q31.1376757 × 1018
95-th percentile1.151181 × 1018
Maximum1.1541792 × 1018
Range1.1541792 × 1018
Interquartile range (IQR)4.1885075 × 1016

Descriptive statistics

Standard deviation2.9252921 × 1016
Coefficient of variation (CV)0.026230802
Kurtosis197.63384
Mean1.1152126 × 1018
Median Absolute Deviation (MAD)2.0905278 × 1016
Skewness-7.0640382
Sum3.2824341 × 1018
Variance8.557334 × 1032
MonotonicityNot monotonic
2025-03-14T23:37:05.217869image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.106727752 × 101811
 
< 0.1%
1.078532699 × 101810
 
< 0.1%
1.098670107 × 101810
 
< 0.1%
1.12012213 × 10189
 
< 0.1%
1.108177162 × 10189
 
< 0.1%
1.098774345 × 10189
 
< 0.1%
1.102767908 × 10189
 
< 0.1%
1.122546022 × 10188
 
< 0.1%
1.136842849 × 10188
 
< 0.1%
1.138994643 × 10188
 
< 0.1%
Other values (744721) 785825
> 99.9%
ValueCountFrequency (%)
53545 1
< 0.1%
843792873 1
< 0.1%
845965787 1
< 0.1%
858130806 1
< 0.1%
870600456 1
< 0.1%
874672381 1
< 0.1%
876070278 1
< 0.1%
885858541 1
< 0.1%
888799721 1
< 0.1%
891656593 1
< 0.1%
ValueCountFrequency (%)
1.154179233 × 10181
< 0.1%
1.154179136 × 10181
< 0.1%
1.154179115 × 10181
< 0.1%
1.154179111 × 10181
< 0.1%
1.154178704 × 10181
< 0.1%
1.154178474 × 10181
< 0.1%
1.154178263 × 10181
< 0.1%
1.154178206 × 10181
< 0.1%
1.15417797 × 10181
< 0.1%
1.154177719 × 10181
< 0.1%

crDate
Date

Distinct686419
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Memory size6.0 MiB
Minimum2006-11-01 03:33:20
Maximum2019-07-24 23:59:07
Invalid dates0
Invalid dates (%)0.0%
2025-03-14T23:37:05.279442image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:05.344884image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

edInput
Categorical

High correlation 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 MiB
-1
422665 
1
215577 
2
106741 
4
 
32733
3
 
8200

Length

Max length2
Median length2
Mean length1.5377992
Min length1

Characters and Unicode

Total characters1208581
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-1
2nd row-1
3rd row-1
4th row-1
5th row-1

Common Values

ValueCountFrequency (%)
-1 422665
53.8%
1 215577
27.4%
2 106741
 
13.6%
4 32733
 
4.2%
3 8200
 
1.0%

Length

2025-03-14T23:37:05.401052image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-14T23:37:05.440625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1 638242
81.2%
2 106741
 
13.6%
4 32733
 
4.2%
3 8200
 
1.0%

Most occurring characters

ValueCountFrequency (%)
1 638242
52.8%
- 422665
35.0%
2 106741
 
8.8%
4 32733
 
2.7%
3 8200
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 785916
65.0%
Dash Punctuation 422665
35.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 638242
81.2%
2 106741
 
13.6%
4 32733
 
4.2%
3 8200
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 422665
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1208581
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 638242
52.8%
- 422665
35.0%
2 106741
 
8.8%
4 32733
 
2.7%
3 8200
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1208581
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 638242
52.8%
- 422665
35.0%
2 106741
 
8.8%
4 32733
 
2.7%
3 8200
 
0.7%

editor
Real number (ℝ)

High correlation 

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2311.9631
Minimum-1
Maximum5101
Zeros0
Zeros (%)0.0%
Negative422665
Negative (%)53.8%
Memory size6.0 MiB
2025-03-14T23:37:05.479023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median-1
Q35003
95-th percentile5007
Maximum5101
Range5102
Interquartile range (IQR)5004

Descriptive statistics

Standard deviation2495.1589
Coefficient of variation (CV)1.0792382
Kurtosis-1.9768935
Mean2311.9631
Median Absolute Deviation (MAD)0
Skewness0.15187097
Sum1.8170088 × 109
Variance6225817.9
MonotonicityNot monotonic
2025-03-14T23:37:05.518574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
-1 422665
53.8%
5004 68536
 
8.7%
5003 68186
 
8.7%
5002 59317
 
7.5%
5001 52629
 
6.7%
5006 40658
 
5.2%
5007 27722
 
3.5%
5005 24934
 
3.2%
5008 21167
 
2.7%
5101 44
 
< 0.1%
Other values (2) 58
 
< 0.1%
ValueCountFrequency (%)
-1 422665
53.8%
1001 36
 
< 0.1%
2001 22
 
< 0.1%
5001 52629
 
6.7%
5002 59317
 
7.5%
5003 68186
 
8.7%
5004 68536
 
8.7%
5005 24934
 
3.2%
5006 40658
 
5.2%
5007 27722
 
3.5%
ValueCountFrequency (%)
5101 44
 
< 0.1%
5008 21167
 
2.7%
5007 27722
3.5%
5006 40658
5.2%
5005 24934
 
3.2%
5004 68536
8.7%
5003 68186
8.7%
5002 59317
7.5%
5001 52629
6.7%
2001 22
 
< 0.1%

engages
Real number (ℝ)

High correlation  Skewed 

Distinct21684
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1403.6372
Minimum0
Maximum4152927
Zeros3406
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2025-03-14T23:37:05.568563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q123
median64
Q3250
95-th percentile3070
Maximum4152927
Range4152927
Interquartile range (IQR)227

Descriptive statistics

Standard deviation16659.603
Coefficient of variation (CV)11.868881
Kurtosis8401.259
Mean1403.6372
Median Absolute Deviation (MAD)52
Skewness62.990607
Sum1.1031409 × 109
Variance2.7754238 × 108
MonotonicityNot monotonic
2025-03-14T23:37:05.625754image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 9949
 
1.3%
10 9876
 
1.3%
11 9863
 
1.3%
8 9840
 
1.3%
9 9764
 
1.2%
13 9748
 
1.2%
14 9715
 
1.2%
15 9587
 
1.2%
7 9501
 
1.2%
6 9472
 
1.2%
Other values (21674) 688601
87.6%
ValueCountFrequency (%)
0 3406
 
0.4%
1 3080
 
0.4%
2 3321
 
0.4%
3 7719
1.0%
4 8695
1.1%
5 9123
1.2%
6 9472
1.2%
7 9501
1.2%
8 9840
1.3%
9 9764
1.2%
ValueCountFrequency (%)
4152927 1
< 0.1%
2447742 1
< 0.1%
2212097 1
< 0.1%
2033066 1
< 0.1%
2013254 1
< 0.1%
1979955 1
< 0.1%
1908389 1
< 0.1%
1685160 1
< 0.1%
1672859 1
< 0.1%
1558032 1
< 0.1%

isApproved
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size767.6 KiB
False
558472 
True
227444 
ValueCountFrequency (%)
False 558472
71.1%
True 227444
28.9%
2025-03-14T23:37:05.663465image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

isEdNeed
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size767.6 KiB
True
785916 
ValueCountFrequency (%)
True 785916
100.0%
2025-03-14T23:37:05.683083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

isRT
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size767.6 KiB
False
651001 
True
134915 
ValueCountFrequency (%)
False 651001
82.8%
True 134915
 
17.2%
2025-03-14T23:37:05.700129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

likes
Real number (ℝ)

High correlation  Skewed 

Distinct19179
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1085.909
Minimum0
Maximum3206434
Zeros4353
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2025-03-14T23:37:05.742514image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q116
median45
Q3184
95-th percentile2347
Maximum3206434
Range3206434
Interquartile range (IQR)168

Descriptive statistics

Standard deviation12939.926
Coefficient of variation (CV)11.916215
Kurtosis7933.3555
Mean1085.909
Median Absolute Deviation (MAD)37
Skewness60.776874
Sum8.5343326 × 108
Variance1.6744167 × 108
MonotonicityNot monotonic
2025-03-14T23:37:05.800590image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 14423
 
1.8%
6 14374
 
1.8%
8 14212
 
1.8%
9 14188
 
1.8%
5 13961
 
1.8%
10 13818
 
1.8%
4 13596
 
1.7%
11 13515
 
1.7%
3 13037
 
1.7%
12 12948
 
1.6%
Other values (19169) 647844
82.4%
ValueCountFrequency (%)
0 4353
 
0.6%
1 6079
0.8%
2 9637
1.2%
3 13037
1.7%
4 13596
1.7%
5 13961
1.8%
6 14374
1.8%
7 14423
1.8%
8 14212
1.8%
9 14188
1.8%
ValueCountFrequency (%)
3206434 1
< 0.1%
1851624 1
< 0.1%
1590522 1
< 0.1%
1582338 1
< 0.1%
1555878 1
< 0.1%
1506312 1
< 0.1%
1302283 1
< 0.1%
1253834 1
< 0.1%
1117840 1
< 0.1%
1108652 1
< 0.1%

photoUrl
URL

Missing 

Distinct255085
Distinct (%)91.8%
Missing508020
Missing (%)64.6%
Memory size40.9 MiB
https://pbs.twimg.com/media/D6v2McUW0AAj24Y.jpg
 
105
https://pbs.twimg.com/media/D2HeMOXWoAAPZmG.jpg
 
104
https://pbs.twimg.com/media/D0cMdWQU0AAsd6h.jpg
 
85
https://pbs.twimg.com/media/CdNsguLW0AEUDX4.jpg
 
72
https://pbs.twimg.com/media/D0C5hQIWoAATvDm.jpg
 
46
Other values (255080)
277484 
(Missing)
508020 
ValueCountFrequency (%)
https://pbs.twimg.com/media/D6v2McUW0AAj24Y.jpg 105
 
< 0.1%
https://pbs.twimg.com/media/D2HeMOXWoAAPZmG.jpg 104
 
< 0.1%
https://pbs.twimg.com/media/D0cMdWQU0AAsd6h.jpg 85
 
< 0.1%
https://pbs.twimg.com/media/CdNsguLW0AEUDX4.jpg 72
 
< 0.1%
https://pbs.twimg.com/media/D0C5hQIWoAATvDm.jpg 46
 
< 0.1%
https://pbs.twimg.com/media/D5N9LEoW0AAsUyJ.jpg 41
 
< 0.1%
https://pbs.twimg.com/media/D5N7u9kWwAArkna.jpg 39
 
< 0.1%
https://pbs.twimg.com/media/D0bw9zmV4AAStDF.jpg 38
 
< 0.1%
https://pbs.twimg.com/media/Dy-hihVWsAEa9l8.jpg 33
 
< 0.1%
https://pbs.twimg.com/media/D1kQj_kW0AEfAIL.jpg 32
 
< 0.1%
Other values (255075) 277301
35.3%
(Missing) 508020
64.6%
ValueCountFrequency (%)
https 277896
35.4%
(Missing) 508020
64.6%
ValueCountFrequency (%)
pbs.twimg.com 277896
35.4%
(Missing) 508020
64.6%
ValueCountFrequency (%)
/media/D6v2McUW0AAj24Y.jpg 105
 
< 0.1%
/media/D2HeMOXWoAAPZmG.jpg 104
 
< 0.1%
/media/D0cMdWQU0AAsd6h.jpg 85
 
< 0.1%
/media/CdNsguLW0AEUDX4.jpg 72
 
< 0.1%
/media/D0C5hQIWoAATvDm.jpg 46
 
< 0.1%
/media/D5N9LEoW0AAsUyJ.jpg 41
 
< 0.1%
/media/D5N7u9kWwAArkna.jpg 39
 
< 0.1%
/media/D0bw9zmV4AAStDF.jpg 38
 
< 0.1%
/media/Dy-hihVWsAEa9l8.jpg 33
 
< 0.1%
/media/D1kQj_kW0AEfAIL.jpg 32
 
< 0.1%
Other values (255075) 277301
35.3%
(Missing) 508020
64.6%
ValueCountFrequency (%)
277896
35.4%
(Missing) 508020
64.6%
ValueCountFrequency (%)
277896
35.4%
(Missing) 508020
64.6%

retweets
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct10589
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean317.7282
Minimum0
Maximum1335638
Zeros26349
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2025-03-14T23:37:05.862085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median18
Q365
95-th percentile692
Maximum1335638
Range1335638
Interquartile range (IQR)59

Descriptive statistics

Standard deviation4053.2674
Coefficient of variation (CV)12.757028
Kurtosis22401.35
Mean317.7282
Median Absolute Deviation (MAD)15
Skewness101.26842
Sum2.4970768 × 108
Variance16428977
MonotonicityNot monotonic
2025-03-14T23:37:05.924225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 32199
 
4.1%
3 31872
 
4.1%
4 30265
 
3.9%
1 30203
 
3.8%
5 28492
 
3.6%
6 26489
 
3.4%
0 26349
 
3.4%
7 24729
 
3.1%
8 22879
 
2.9%
9 20728
 
2.6%
Other values (10579) 511711
65.1%
ValueCountFrequency (%)
0 26349
3.4%
1 30203
3.8%
2 32199
4.1%
3 31872
4.1%
4 30265
3.9%
5 28492
3.6%
6 26489
3.4%
7 24729
3.1%
8 22879
2.9%
9 20728
2.6%
ValueCountFrequency (%)
1335638 1
< 0.1%
946493 1
< 0.1%
621575 1
< 0.1%
596118 1
< 0.1%
564207 1
< 0.1%
511486 1
< 0.1%
473643 1
< 0.1%
457376 1
< 0.1%
450728 1
< 0.1%
382877 1
< 0.1%

rtUsID
Real number (ℝ)

High correlation 

Distinct639
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3650976 × 1016
Minimum-1
Maximum1.108957 × 1018
Zeros0
Zeros (%)0.0%
Negative651001
Negative (%)82.8%
Memory size6.0 MiB
2025-03-14T23:37:05.984711image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median-1
Q3-1
95-th percentile7.007845 × 1017
Maximum1.108957 × 1018
Range1.108957 × 1018
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.8943837 × 1017
Coefficient of variation (CV)4.3398426
Kurtosis15.379328
Mean4.3650976 × 1016
Median Absolute Deviation (MAD)0
Skewness4.1480429
Sum-4.9433192 × 1018
Variance3.5886895 × 1034
MonotonicityNot monotonic
2025-03-14T23:37:06.048550image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1 651001
82.8%
20562637 7381
 
0.9%
34713362 5476
 
0.7%
807095 4022
 
0.5%
7.814273015 × 10174019
 
0.5%
1235663514 3866
 
0.5%
25453312 3785
 
0.5%
8.585161114 × 10173351
 
0.4%
2866476539 2747
 
0.3%
8.657665192 × 10172709
 
0.3%
Other values (629) 97559
 
12.4%
ValueCountFrequency (%)
-1 651001
82.8%
428333 436
 
0.1%
621523 335
 
< 0.1%
621583 10
 
< 0.1%
624413 25
 
< 0.1%
742143 559
 
0.1%
759251 188
 
< 0.1%
807095 4022
 
0.5%
809760 9
 
< 0.1%
816653 83
 
< 0.1%
ValueCountFrequency (%)
1.108957041 × 10184
 
< 0.1%
1.101825687 × 101862
 
< 0.1%
1.066832136 × 101813
 
< 0.1%
1.062791226 × 101810
 
< 0.1%
1.061553475 × 10181
 
< 0.1%
1.05844362 × 101859
 
< 0.1%
1.04833502 × 101827
 
< 0.1%
1.047630407 × 101892
< 0.1%
1.045103187 × 1018166
< 0.1%
1.041537348 × 10189
 
< 0.1%

text
Text

Distinct710522
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size216.7 MiB
2025-03-14T23:37:06.822120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length968
Median length352
Mean length130.86807
Min length4

Characters and Unicode

Total characters102851311
Distinct characters2561
Distinct categories23 ?
Distinct scripts23 ?
Distinct blocks56 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique666155 ?
Unique (%)84.8%

Sample

1st rowThe immediate impulse for an alliance of the EU's northern states is Brexit https://t.co/nlhUD36hay https://t.co/shwMWpjjuK
2nd rowAmerica's economy is flashing some warning signs, but -- for now -- the labor market appears to be going strong https://t.co/xvCPgtqMzy https://t.co/0sQdzAsME3
3rd rowLyft files for what is expected to be one of the hottest IPOs in 2019 https://t.co/qEjyniazlD
4th rowExporters still waiting to get Rs 6,000 crore worth of input tax credit refunds Many being denied tax refunds by state governments, such as Andhra Pradesh, Uttar Pradesh, Bihar and Chhattisgarh, who say they are cash starved @Subhayan_ism @GST_Council https://t.co/QRBg8b98Rr
5th rowRide-hailing firm Lyft races to leave Uber behind in IPO chase https://t.co/0qCsdx2LYS https://t.co/gHZLUntYkL
ValueCountFrequency (%)
the 524924
 
3.7%
to 339238
 
2.4%
a 288969
 
2.0%
of 255689
 
1.8%
in 220648
 
1.6%
and 211586
 
1.5%
is 160255
 
1.1%
for 139028
 
1.0%
you 127547
 
0.9%
124246
 
0.9%
Other values (1076361) 11836996
83.2%
2025-03-14T23:37:07.663755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13304640
 
12.9%
t 7991076
 
7.8%
e 7374871
 
7.2%
o 5977026
 
5.8%
a 5137798
 
5.0%
s 5093770
 
5.0%
i 4680619
 
4.6%
n 4483766
 
4.4%
r 4188907
 
4.1%
h 3602956
 
3.5%
Other values (2551) 41015882
39.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 71198390
69.2%
Space Separator 13317519
 
12.9%
Uppercase Letter 8118612
 
7.9%
Other Punctuation 6807706
 
6.6%
Decimal Number 2123334
 
2.1%
Control 435896
 
0.4%
Dash Punctuation 223873
 
0.2%
Other Symbol 211993
 
0.2%
Final Punctuation 143098
 
0.1%
Currency Symbol 52005
 
0.1%
Other values (13) 218885
 
0.2%

Most frequent character per category

Other Symbol
ValueCountFrequency (%)
25445
 
12.0%
😍 11423
 
5.4%
👉 8437
 
4.0%
😂 6218
 
2.9%
🔥 4996
 
2.4%
4082
 
1.9%
3836
 
1.8%
3727
 
1.8%
📷 3385
 
1.6%
3056
 
1.4%
Other values (1213) 137388
64.8%
Lowercase Letter
ValueCountFrequency (%)
t 7991076
11.2%
e 7374871
 
10.4%
o 5977026
 
8.4%
a 5137798
 
7.2%
s 5093770
 
7.2%
i 4680619
 
6.6%
n 4483766
 
6.3%
r 4188907
 
5.9%
h 3602956
 
5.1%
c 2813206
 
4.0%
Other values (405) 19854395
27.9%
Other Letter
ValueCountFrequency (%)
48
 
3.3%
48
 
3.3%
45
 
3.1%
45
 
3.1%
45
 
3.1%
37
 
2.5%
32
 
2.2%
22
 
1.5%
º 21
 
1.4%
21
 
1.4%
Other values (392) 1092
75.0%
Uppercase Letter
ValueCountFrequency (%)
T 576653
 
7.1%
S 499116
 
6.1%
A 482271
 
5.9%
I 432482
 
5.3%
C 427195
 
5.3%
M 385985
 
4.8%
B 375685
 
4.6%
P 334097
 
4.1%
W 332611
 
4.1%
D 330659
 
4.1%
Other values (197) 3941858
48.6%
Modifier Letter
ValueCountFrequency (%)
187
 
10.8%
160
 
9.2%
96
 
5.5%
88
 
5.1%
ʰ 85
 
4.9%
ˢ 84
 
4.8%
80
 
4.6%
78
 
4.5%
69
 
4.0%
64
 
3.7%
Other values (52) 742
42.8%
Math Symbol
ValueCountFrequency (%)
> 22140
48.6%
| 13056
28.6%
+ 6565
 
14.4%
~ 1830
 
4.0%
= 1252
 
2.7%
< 300
 
0.7%
171
 
0.4%
87
 
0.2%
× 72
 
0.2%
11
 
< 0.1%
Other values (33) 115
 
0.3%
Other Punctuation
ValueCountFrequency (%)
/ 2727718
40.1%
. 1515882
22.3%
: 1040397
 
15.3%
# 407266
 
6.0%
, 383111
 
5.6%
' 231499
 
3.4%
@ 226945
 
3.3%
" 96126
 
1.4%
! 73119
 
1.1%
? 51062
 
0.8%
Other values (31) 54581
 
0.8%
Decimal Number
ValueCountFrequency (%)
0 309010
14.6%
1 274281
12.9%
2 242656
11.4%
5 199786
9.4%
9 198002
9.3%
3 190132
9.0%
4 180651
8.5%
8 178767
8.4%
7 175510
8.3%
6 174493
8.2%
Other values (20) 46
 
< 0.1%
Nonspacing Mark
ValueCountFrequency (%)
19187
99.0%
117
 
0.6%
͜ 14
 
0.1%
̵ 13
 
0.1%
̶ 13
 
0.1%
͡ 11
 
0.1%
3
 
< 0.1%
͞ 3
 
< 0.1%
2
 
< 0.1%
2
 
< 0.1%
Other values (10) 11
 
0.1%
Format
ValueCountFrequency (%)
3186
44.7%
1287
18.0%
1275
17.9%
455
 
6.4%
203
 
2.8%
146
 
2.0%
󠁧 120
 
1.7%
󠁿 91
 
1.3%
󠁢 91
 
1.3%
󠁳 63
 
0.9%
Other values (10) 218
 
3.1%
Modifier Symbol
ValueCountFrequency (%)
🏻 2175
44.9%
🏼 1316
27.2%
🏽 382
 
7.9%
^ 248
 
5.1%
229
 
4.7%
🏾 202
 
4.2%
` 142
 
2.9%
¯ 56
 
1.2%
´ 38
 
0.8%
🏿 35
 
0.7%
Other values (6) 21
 
0.4%
Other Number
ValueCountFrequency (%)
² 23
28.0%
½ 23
28.0%
12
14.6%
¼ 6
 
7.3%
³ 4
 
4.9%
3
 
3.7%
2
 
2.4%
2
 
2.4%
2
 
2.4%
2
 
2.4%
Other values (3) 3
 
3.7%
Open Punctuation
ValueCountFrequency (%)
( 25891
78.7%
[ 6074
 
18.5%
{ 882
 
2.7%
17
 
0.1%
7
 
< 0.1%
7
 
< 0.1%
3
 
< 0.1%
2
 
< 0.1%
︿ 2
 
< 0.1%
2
 
< 0.1%
Other values (2) 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
13304640
99.9%
  12370
 
0.1%
  339
 
< 0.1%
107
 
< 0.1%
27
 
< 0.1%
14
 
< 0.1%
10
 
< 0.1%
7
 
< 0.1%
5
 
< 0.1%
Currency Symbol
ValueCountFrequency (%)
$ 50659
97.4%
£ 1195
 
2.3%
118
 
0.2%
17
 
< 0.1%
¥ 7
 
< 0.1%
¢ 5
 
< 0.1%
฿ 2
 
< 0.1%
1
 
< 0.1%
1
 
< 0.1%
Control
ValueCountFrequency (%)
435833
> 99.9%
 22
 
< 0.1%
20
 
< 0.1%
– 8
 
< 0.1%
— 4
 
< 0.1%
” 4
 
< 0.1%
“ 4
 
< 0.1%
’ 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 194513
86.9%
22073
 
9.9%
6136
 
2.7%
1130
 
0.5%
16
 
< 0.1%
2
 
< 0.1%
2
 
< 0.1%
1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 28291
80.2%
] 6042
 
17.1%
} 903
 
2.6%
10
 
< 0.1%
7
 
< 0.1%
4
 
< 0.1%
2
 
< 0.1%
2
 
< 0.1%
Final Punctuation
ValueCountFrequency (%)
117374
82.0%
25609
 
17.9%
» 112
 
0.1%
3
 
< 0.1%
Connector Punctuation
ValueCountFrequency (%)
_ 32598
99.3%
_ 224
 
0.7%
5
 
< 0.1%
Initial Punctuation
ValueCountFrequency (%)
26497
70.7%
10869
29.0%
« 108
 
0.3%
Private Use
ValueCountFrequency (%)
󲝤 4
66.7%
1
 
16.7%
1
 
16.7%
Enclosing Mark
ValueCountFrequency (%)
199
98.0%
҉ 4
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 79313384
77.1%
Common 23488126
 
22.8%
Braille 25445
 
< 0.1%
Inherited 22747
 
< 0.1%
Han 669
 
< 0.1%
Katakana 331
 
< 0.1%
Hiragana 126
 
< 0.1%
Hangul 110
 
< 0.1%
Cyrillic 86
 
< 0.1%
Arabic 86
 
< 0.1%
Other values (13) 201
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
13304640
56.6%
/ 2727718
 
11.6%
. 1515882
 
6.5%
: 1040397
 
4.4%
435833
 
1.9%
# 407266
 
1.7%
, 383111
 
1.6%
0 309010
 
1.3%
1 274281
 
1.2%
2 242656
 
1.0%
Other values (1828) 2847332
 
12.1%
Latin
ValueCountFrequency (%)
t 7991076
 
10.1%
e 7374871
 
9.3%
o 5977026
 
7.5%
a 5137798
 
6.5%
s 5093770
 
6.4%
i 4680619
 
5.9%
n 4483766
 
5.7%
r 4188907
 
5.3%
h 3602956
 
4.5%
c 2813206
 
3.5%
Other values (241) 27969389
35.3%
Han
ValueCountFrequency (%)
48
 
7.2%
48
 
7.2%
45
 
6.7%
45
 
6.7%
45
 
6.7%
20
 
3.0%
15
 
2.2%
15
 
2.2%
13
 
1.9%
12
 
1.8%
Other values (185) 363
54.3%
Hangul
ValueCountFrequency (%)
14
 
12.7%
12
 
10.9%
6
 
5.5%
6
 
5.5%
6
 
5.5%
5
 
4.5%
3
 
2.7%
3
 
2.7%
2
 
1.8%
2
 
1.8%
Other values (39) 51
46.4%
Katakana
ValueCountFrequency (%)
37
 
11.2%
32
 
9.7%
22
 
6.6%
21
 
6.3%
18
 
5.4%
17
 
5.1%
16
 
4.8%
16
 
4.8%
13
 
3.9%
12
 
3.6%
Other values (36) 127
38.4%
Cyrillic
ValueCountFrequency (%)
ү 28
32.6%
С 7
 
8.1%
с 6
 
7.0%
ғ 4
 
4.7%
҉ 4
 
4.7%
и 4
 
4.7%
о 4
 
4.7%
а 3
 
3.5%
Х 2
 
2.3%
в 2
 
2.3%
Other values (20) 22
25.6%
Thai
ValueCountFrequency (%)
9
13.8%
8
 
12.3%
6
 
9.2%
4
 
6.2%
3
 
4.6%
3
 
4.6%
3
 
4.6%
3
 
4.6%
3
 
4.6%
2
 
3.1%
Other values (17) 21
32.3%
Hiragana
ValueCountFrequency (%)
17
13.5%
15
11.9%
14
11.1%
10
 
7.9%
9
 
7.1%
8
 
6.3%
6
 
4.8%
5
 
4.0%
4
 
3.2%
4
 
3.2%
Other values (16) 34
27.0%
Arabic
ValueCountFrequency (%)
و 11
12.8%
ل 11
12.8%
ا 11
12.8%
ي 9
10.5%
ن 7
 
8.1%
ر 6
 
7.0%
م 4
 
4.7%
ئ 3
 
3.5%
س 3
 
3.5%
ج 3
 
3.5%
Other values (15) 18
20.9%
Canadian_Aboriginal
ValueCountFrequency (%)
4
 
10.3%
4
 
10.3%
3
 
7.7%
3
 
7.7%
3
 
7.7%
2
 
5.1%
2
 
5.1%
2
 
5.1%
2
 
5.1%
2
 
5.1%
Other values (12) 12
30.8%
Hebrew
ValueCountFrequency (%)
א 2
15.4%
ש 1
7.7%
ִ 1
7.7%
ׁ 1
7.7%
֖ 1
7.7%
י 1
7.7%
ת 1
7.7%
ֵ 1
7.7%
ב 1
7.7%
ְ 1
7.7%
Other values (2) 2
15.4%
Inherited
ValueCountFrequency (%)
19187
84.3%
3186
 
14.0%
199
 
0.9%
117
 
0.5%
͜ 14
 
0.1%
̵ 13
 
0.1%
̶ 13
 
0.1%
͡ 11
 
< 0.1%
4
 
< 0.1%
͞ 3
 
< 0.1%
Greek
ValueCountFrequency (%)
π 7
36.8%
ω 3
15.8%
α 3
15.8%
θ 1
 
5.3%
1
 
5.3%
γ 1
 
5.3%
β 1
 
5.3%
Λ 1
 
5.3%
μ 1
 
5.3%
Devanagari
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Unknown
ValueCountFrequency (%)
󲝤 4
66.7%
1
 
16.7%
1
 
16.7%
Tibetan
ValueCountFrequency (%)
2
33.3%
2
33.3%
2
33.3%
Egyptian_Hieroglyphs
ValueCountFrequency (%)
𓅃 1
33.3%
𓂀 1
33.3%
𓁁 1
33.3%
Braille
ValueCountFrequency (%)
25445
100.0%
Armenian
ValueCountFrequency (%)
֎ 24
100.0%
Oriya
ValueCountFrequency (%)
7
100.0%
Georgian
ValueCountFrequency (%)
7
100.0%
Lao
ValueCountFrequency (%)
4
100.0%
Kannada
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 102363049
99.5%
Punctuation 222247
 
0.2%
None 130473
 
0.1%
Emoticons 40413
 
< 0.1%
Braille 25445
 
< 0.1%
VS 19304
 
< 0.1%
Dingbats 17815
 
< 0.1%
Enclosed Alphanum Sup 10271
 
< 0.1%
Misc Symbols 7807
 
< 0.1%
Math Alphanum 5128
 
< 0.1%
Other values (46) 9359
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13304640
 
13.0%
t 7991076
 
7.8%
e 7374871
 
7.2%
o 5977026
 
5.8%
a 5137798
 
5.0%
s 5093770
 
5.0%
i 4680619
 
4.6%
n 4483766
 
4.4%
r 4188907
 
4.1%
h 3602956
 
3.5%
Other values (87) 40527620
39.6%
Punctuation
ValueCountFrequency (%)
117374
52.8%
26497
 
11.9%
25609
 
11.5%
22073
 
9.9%
10869
 
4.9%
6136
 
2.8%
3186
 
1.4%
3091
 
1.4%
2488
 
1.1%
1287
 
0.6%
Other values (24) 3637
 
1.6%
Braille
ValueCountFrequency (%)
25445
100.0%
VS
ValueCountFrequency (%)
19187
99.4%
117
 
0.6%
None
ValueCountFrequency (%)
  12370
 
9.5%
👉 8437
 
6.5%
🔥 4996
 
3.8%
📷 3385
 
2.6%
🤣 2659
 
2.0%
📸 2238
 
1.7%
🏻 2175
 
1.7%
2159
 
1.7%
👇 2075
 
1.6%
é 1925
 
1.5%
Other values (1058) 88054
67.5%
Emoticons
ValueCountFrequency (%)
😍 11423
28.3%
😂 6218
15.4%
😊 2230
 
5.5%
😫 1539
 
3.8%
😭 1484
 
3.7%
😱 1447
 
3.6%
😘 1335
 
3.3%
😲 1132
 
2.8%
🙌 1130
 
2.8%
🙍 918
 
2.3%
Other values (70) 11557
28.6%
Dingbats
ValueCountFrequency (%)
4082
22.9%
3836
21.5%
3727
20.9%
3056
17.2%
995
 
5.6%
433
 
2.4%
340
 
1.9%
324
 
1.8%
207
 
1.2%
116
 
0.7%
Other values (39) 699
 
3.9%
Misc Symbols
ValueCountFrequency (%)
1505
19.3%
901
11.5%
820
 
10.5%
662
 
8.5%
390
 
5.0%
376
 
4.8%
362
 
4.6%
304
 
3.9%
184
 
2.4%
126
 
1.6%
Other values (81) 2177
27.9%
Enclosed Alphanum Sup
ValueCountFrequency (%)
🇸 1179
 
11.5%
🇺 1125
 
11.0%
🇮 773
 
7.5%
🇷 767
 
7.5%
🇹 564
 
5.5%
🇳 560
 
5.5%
🇦 537
 
5.2%
🇨 489
 
4.8%
🇬 463
 
4.5%
🇪 442
 
4.3%
Other values (22) 3372
32.8%
Specials
ValueCountFrequency (%)
785
98.7%
10
 
1.3%
Geometric Shapes
ValueCountFrequency (%)
519
41.0%
342
27.0%
193
 
15.3%
61
 
4.8%
25
 
2.0%
18
 
1.4%
18
 
1.4%
15
 
1.2%
9
 
0.7%
9
 
0.7%
Other values (17) 56
 
4.4%
Misc Technical
ValueCountFrequency (%)
322
40.1%
191
23.8%
87
 
10.8%
55
 
6.8%
39
 
4.9%
33
 
4.1%
25
 
3.1%
20
 
2.5%
8
 
1.0%
6
 
0.7%
Other values (10) 17
 
2.1%
Math Alphanum
ValueCountFrequency (%)
𝑒 209
 
4.1%
𝑖 146
 
2.8%
𝑎 144
 
2.8%
𝑛 129
 
2.5%
𝑜 127
 
2.5%
𝑡 125
 
2.4%
𝑠 124
 
2.4%
𝑟 117
 
2.3%
𝚎 88
 
1.7%
𝚘 78
 
1.5%
Other values (390) 3841
74.9%
Phonetic Ext
ValueCountFrequency (%)
187
17.2%
160
14.7%
96
 
8.8%
88
 
8.1%
78
 
7.2%
64
 
5.9%
55
 
5.1%
39
 
3.6%
36
 
3.3%
24
 
2.2%
Other values (34) 262
24.1%
Box Drawing
ValueCountFrequency (%)
187
13.5%
134
9.7%
126
9.1%
122
8.8%
121
8.8%
117
8.5%
80
 
5.8%
80
 
5.8%
78
 
5.6%
64
 
4.6%
Other values (15) 272
19.7%
Arrows
ValueCountFrequency (%)
171
64.3%
24
 
9.0%
22
 
8.3%
11
 
4.1%
10
 
3.8%
7
 
2.6%
5
 
1.9%
3
 
1.1%
3
 
1.1%
2
 
0.8%
Other values (7) 8
 
3.0%
Block Elements
ValueCountFrequency (%)
140
40.8%
87
25.4%
31
 
9.0%
30
 
8.7%
20
 
5.8%
19
 
5.5%
6
 
1.7%
4
 
1.2%
3
 
0.9%
3
 
0.9%
Tags
ValueCountFrequency (%)
󠁧 120
21.8%
󠁿 91
16.5%
󠁢 91
16.5%
󠁳 63
11.5%
󠁣 48
 
8.7%
󠁴 47
 
8.5%
󠁮 29
 
5.3%
󠁥 29
 
5.3%
󠁷 15
 
2.7%
󠁬 15
 
2.7%
Other values (2) 2
 
0.4%
Currency Symbols
ValueCountFrequency (%)
118
86.1%
17
 
12.4%
1
 
0.7%
1
 
0.7%
Letterlike Symbols
ValueCountFrequency (%)
95
35.4%
75
28.0%
73
27.2%
12
 
4.5%
7
 
2.6%
2
 
0.7%
1
 
0.4%
1
 
0.4%
1
 
0.4%
1
 
0.4%
Modifier Letters
ValueCountFrequency (%)
ʰ 85
19.7%
ˢ 84
19.5%
ʳ 61
14.2%
ˡ 58
13.5%
ʷ 55
12.8%
ʸ 45
10.4%
ʻ 10
 
2.3%
˚ 8
 
1.9%
ʺ 7
 
1.6%
ʲ 5
 
1.2%
Other values (7) 13
 
3.0%
CJK
ValueCountFrequency (%)
48
 
7.2%
48
 
7.2%
45
 
6.7%
45
 
6.7%
45
 
6.7%
20
 
3.0%
15
 
2.2%
15
 
2.2%
13
 
1.9%
12
 
1.8%
Other values (185) 363
54.3%
Katakana
ValueCountFrequency (%)
46
 
11.5%
37
 
9.3%
32
 
8.0%
26
 
6.5%
22
 
5.5%
21
 
5.3%
18
 
4.5%
17
 
4.3%
16
 
4.0%
16
 
4.0%
Other values (36) 148
37.1%
Phonetic Ext Sup
ValueCountFrequency (%)
39
37.5%
38
36.5%
24
23.1%
3
 
2.9%
Cyrillic
ValueCountFrequency (%)
ү 28
32.6%
С 7
 
8.1%
с 6
 
7.0%
ғ 4
 
4.7%
҉ 4
 
4.7%
и 4
 
4.7%
о 4
 
4.7%
а 3
 
3.5%
Х 2
 
2.3%
в 2
 
2.3%
Other values (20) 22
25.6%
Armenian
ValueCountFrequency (%)
֎ 24
100.0%
IPA Ext
ValueCountFrequency (%)
ʀ 20
19.4%
ʜ 20
19.4%
ʖ 11
10.7%
ɪ 8
 
7.8%
ʇ 7
 
6.8%
ɹ 5
 
4.9%
ə 5
 
4.9%
ɥ 4
 
3.9%
ɐ 4
 
3.9%
ɴ 3
 
2.9%
Other values (11) 16
15.5%
Hiragana
ValueCountFrequency (%)
17
12.7%
15
 
11.2%
14
 
10.4%
10
 
7.5%
9
 
6.7%
8
 
6.0%
8
 
6.0%
6
 
4.5%
5
 
3.7%
4
 
3.0%
Other values (17) 38
28.4%
Playing Cards
ValueCountFrequency (%)
🃏 17
100.0%
Compat Jamo
ValueCountFrequency (%)
14
53.8%
12
46.2%
Diacriticals
ValueCountFrequency (%)
͜ 14
25.9%
̵ 13
24.1%
̶ 13
24.1%
͡ 11
20.4%
͞ 3
 
5.6%
Arabic
ValueCountFrequency (%)
و 11
12.6%
ل 11
12.6%
ا 11
12.6%
ي 9
10.3%
ن 7
 
8.0%
ر 6
 
6.9%
م 4
 
4.6%
ئ 3
 
3.4%
س 3
 
3.4%
ج 3
 
3.4%
Other values (16) 19
21.8%
CJK Compat Forms
ValueCountFrequency (%)
10
76.9%
︿ 2
 
15.4%
1
 
7.7%
Thai
ValueCountFrequency (%)
9
 
13.4%
8
 
11.9%
6
 
9.0%
4
 
6.0%
3
 
4.5%
3
 
4.5%
3
 
4.5%
3
 
4.5%
3
 
4.5%
2
 
3.0%
Other values (18) 23
34.3%
Alphabetic PF
ValueCountFrequency (%)
8
88.9%
1
 
11.1%
Oriya
ValueCountFrequency (%)
7
100.0%
Georgian
ValueCountFrequency (%)
7
100.0%
Hangul
ValueCountFrequency (%)
6
 
7.1%
6
 
7.1%
6
 
7.1%
5
 
6.0%
3
 
3.6%
3
 
3.6%
2
 
2.4%
2
 
2.4%
2
 
2.4%
2
 
2.4%
Other values (37) 47
56.0%
Math Operators
ValueCountFrequency (%)
6
15.0%
6
15.0%
4
10.0%
4
10.0%
4
10.0%
4
10.0%
4
10.0%
2
 
5.0%
2
 
5.0%
1
 
2.5%
Other values (3) 3
7.5%
Lao
ValueCountFrequency (%)
4
100.0%
UCAS
ValueCountFrequency (%)
4
 
10.3%
4
 
10.3%
3
 
7.7%
3
 
7.7%
3
 
7.7%
2
 
5.1%
2
 
5.1%
2
 
5.1%
2
 
5.1%
2
 
5.1%
Other values (12) 12
30.8%
Latin Ext Additional
ValueCountFrequency (%)
3
37.5%
3
37.5%
1
 
12.5%
1
 
12.5%
Number Forms
ValueCountFrequency (%)
3
100.0%
Kannada
ValueCountFrequency (%)
2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
2
25.0%
2
25.0%
2
25.0%
1
12.5%
1
12.5%
Tibetan
ValueCountFrequency (%)
2
33.3%
2
33.3%
2
33.3%
Hebrew
ValueCountFrequency (%)
א 2
15.4%
ש 1
7.7%
ִ 1
7.7%
ׁ 1
7.7%
֖ 1
7.7%
י 1
7.7%
ת 1
7.7%
ֵ 1
7.7%
ב 1
7.7%
ְ 1
7.7%
Other values (2) 2
15.4%
Small Forms
ValueCountFrequency (%)
2
100.0%
CJK Compat
ValueCountFrequency (%)
1
100.0%
Devanagari
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Enclosed Ideographic Sup
ValueCountFrequency (%)
🉐 1
100.0%
Mahjong
ValueCountFrequency (%)
🀄 1
100.0%
Egyptian Hieroglyphs
ValueCountFrequency (%)
𓅃 1
33.3%
𓂀 1
33.3%
𓁁 1
33.3%
PUA
ValueCountFrequency (%)
1
50.0%
1
50.0%
Geometric Shapes Ext
ValueCountFrequency (%)
🟡 1
100.0%
Domino
ValueCountFrequency (%)
🀹 1
100.0%

topicName
Categorical

Distinct42
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size43.2 MiB
Business
164602 
News
131973 
Motivational
84750 
Technology
47679 
Design & Architecture
44987 
Other values (37)
311925 

Length

Max length24
Median length16
Mean length8.6531054
Min length3

Characters and Unicode

Total characters6800614
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowBusiness
2nd rowBusiness
3rd rowBusiness
4th rowBusiness
5th rowBusiness

Common Values

ValueCountFrequency (%)
Business 164602
20.9%
News 131973
16.8%
Motivational 84750
10.8%
Technology 47679
 
6.1%
Design & Architecture 44987
 
5.7%
Cryptocurrency 38623
 
4.9%
Art 36697
 
4.7%
Interesting 28615
 
3.6%
Animal 28202
 
3.6%
Memes 26349
 
3.4%
Other values (32) 153439
19.5%

Length

2025-03-14T23:37:07.724145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
business 164602
17.6%
news 132252
14.2%
motivational 84750
 
9.1%
67473
 
7.2%
technology 47679
 
5.1%
design 44987
 
4.8%
architecture 44987
 
4.8%
cryptocurrency 38623
 
4.1%
art 36697
 
3.9%
interesting 28615
 
3.1%
Other values (39) 242297
26.0%

Most occurring characters

ValueCountFrequency (%)
s 758810
 
11.2%
e 699171
 
10.3%
i 520692
 
7.7%
n 515001
 
7.6%
t 478590
 
7.0%
o 386155
 
5.7%
r 378225
 
5.6%
a 321111
 
4.7%
u 290216
 
4.3%
c 242622
 
3.6%
Other values (33) 2210021
32.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5675787
83.5%
Uppercase Letter 910308
 
13.4%
Space Separator 147046
 
2.2%
Other Punctuation 67473
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 758810
13.4%
e 699171
12.3%
i 520692
9.2%
n 515001
9.1%
t 478590
8.4%
o 386155
 
6.8%
r 378225
 
6.7%
a 321111
 
5.7%
u 290216
 
5.1%
c 242622
 
4.3%
Other values (12) 1085194
19.1%
Uppercase Letter
ValueCountFrequency (%)
B 164680
18.1%
N 158065
17.4%
M 114072
12.5%
A 109886
12.1%
D 67511
7.4%
C 61015
 
6.7%
T 60894
 
6.7%
I 51125
 
5.6%
P 35247
 
3.9%
F 25569
 
2.8%
Other values (9) 62244
 
6.8%
Space Separator
ValueCountFrequency (%)
147046
100.0%
Other Punctuation
ValueCountFrequency (%)
& 67473
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6586095
96.8%
Common 214519
 
3.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 758810
 
11.5%
e 699171
 
10.6%
i 520692
 
7.9%
n 515001
 
7.8%
t 478590
 
7.3%
o 386155
 
5.9%
r 378225
 
5.7%
a 321111
 
4.9%
u 290216
 
4.4%
c 242622
 
3.7%
Other values (31) 1995502
30.3%
Common
ValueCountFrequency (%)
147046
68.5%
& 67473
31.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6800614
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 758810
 
11.2%
e 699171
 
10.3%
i 520692
 
7.7%
n 515001
 
7.6%
t 478590
 
7.0%
o 386155
 
5.7%
r 378225
 
5.6%
a 321111
 
4.7%
u 290216
 
4.3%
c 242622
 
3.6%
Other values (33) 2210021
32.5%

usFlwrs
Real number (ℝ)

High correlation 

Distinct343319
Distinct (%)43.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4472701.3
Minimum0
Maximum1.0573845 × 108
Zeros60
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2025-03-14T23:37:07.780344image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2472
Q1142628
median966826.5
Q33603135
95-th percentile20591725
Maximum1.0573845 × 108
Range1.0573845 × 108
Interquartile range (IQR)3460507

Descriptive statistics

Standard deviation9149778.1
Coefficient of variation (CV)2.045694
Kurtosis11.068883
Mean4472701.3
Median Absolute Deviation (MAD)961332.5
Skewness3.2684972
Sum3.5151675 × 1012
Variance8.371844 × 1013
MonotonicityNot monotonic
2025-03-14T23:37:07.841176image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
590529 234
 
< 0.1%
16262182 217
 
< 0.1%
589918 211
 
< 0.1%
2150418 191
 
< 0.1%
2133253 187
 
< 0.1%
62 181
 
< 0.1%
590441 162
 
< 0.1%
590390 150
 
< 0.1%
16235969 148
 
< 0.1%
65 147
 
< 0.1%
Other values (343309) 784088
99.8%
ValueCountFrequency (%)
0 60
< 0.1%
1 49
< 0.1%
2 59
< 0.1%
3 53
< 0.1%
4 61
< 0.1%
5 59
< 0.1%
6 67
< 0.1%
7 51
< 0.1%
8 59
< 0.1%
9 66
< 0.1%
ValueCountFrequency (%)
105738450 1
< 0.1%
105246986 1
< 0.1%
105246692 1
< 0.1%
105245851 1
< 0.1%
105017221 1
< 0.1%
103922950 1
< 0.1%
103873045 1
< 0.1%
103873020 2
< 0.1%
103744375 1
< 0.1%
103670138 2
< 0.1%

usID
Real number (ℝ)

High correlation 

Distinct22516
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0852761 × 1017
Minimum12
Maximum1.153467 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2025-03-14T23:37:07.899744image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile1652541
Q115513767
median36184220
Q39.545908 × 108
95-th percentile9.4275497 × 1017
Maximum1.153467 × 1018
Range1.153467 × 1018
Interquartile range (IQR)9.3907704 × 108

Descriptive statistics

Standard deviation3.0104857 × 1017
Coefficient of variation (CV)2.7739352
Kurtosis4.195324
Mean1.0852761 × 1017
Median Absolute Deviation (MAD)35377125
Skewness2.460755
Sum-4.1567913 × 1018
Variance9.063024 × 1034
MonotonicityNot monotonic
2025-03-14T23:37:07.961182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34713362 62033
 
7.9%
200583835 37446
 
4.8%
20562637 36255
 
4.6%
14763734 22131
 
2.8%
3108351 20364
 
2.6%
807095 16862
 
2.1%
14511951 15798
 
2.0%
1652541 14897
 
1.9%
701725963 14727
 
1.9%
16896485 14412
 
1.8%
Other values (22506) 530991
67.6%
ValueCountFrequency (%)
12 8
< 0.1%
62 1
 
< 0.1%
767 7
< 0.1%
1585 3
 
< 0.1%
1605 3
 
< 0.1%
3475 1
 
< 0.1%
4816 2
 
< 0.1%
7846 1
 
< 0.1%
10221 1
 
< 0.1%
10437 1
 
< 0.1%
ValueCountFrequency (%)
1.153466973 × 10181
 
< 0.1%
1.152826439 × 10181
 
< 0.1%
1.152685127 × 10181
 
< 0.1%
1.152301169 × 10181
 
< 0.1%
1.152284678 × 10182
 
< 0.1%
1.151881037 × 10181
 
< 0.1%
1.15169615 × 10181
 
< 0.1%
1.151607491 × 10181
 
< 0.1%
1.151507737 × 101816
< 0.1%
1.151473541 × 10181
 
< 0.1%

usName
Text

Distinct22978
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size51.0 MiB
2025-03-14T23:37:08.112521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length50
Median length44
Mean length12.720442
Min length1

Characters and Unicode

Total characters9997199
Distinct characters1823
Distinct categories23 ?
Distinct scripts25 ?
Distinct blocks53 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12921 ?
Unique (%)1.6%

Sample

1st rowThe Economist
2nd rowCNN Business
3rd rowFORTUNE
4th rowBusiness Standard
5th rowReuters Business
ValueCountFrequency (%)
bloomberg 66759
 
4.2%
the 63271
 
4.0%
business 53561
 
3.4%
insider 42829
 
2.7%
tim 37593
 
2.4%
fargo 37447
 
2.4%
news 32959
 
2.1%
reuters 28544
 
1.8%
quotes 25315
 
1.6%
digital 22231
 
1.4%
Other values (21870) 1179163
74.2%
2025-03-14T23:37:08.332873image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 951284
 
9.5%
804352
 
8.0%
o 617337
 
6.2%
i 606223
 
6.1%
r 604599
 
6.0%
s 600581
 
6.0%
a 512714
 
5.1%
n 499289
 
5.0%
t 436832
 
4.4%
l 383455
 
3.8%
Other values (1813) 3980533
39.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7168105
71.7%
Uppercase Letter 1821774
 
18.2%
Space Separator 804423
 
8.0%
Other Symbol 85207
 
0.9%
Other Punctuation 58912
 
0.6%
Decimal Number 19252
 
0.2%
Nonspacing Mark 11467
 
0.1%
Connector Punctuation 8458
 
0.1%
Dash Punctuation 5221
 
0.1%
Close Punctuation 2981
 
< 0.1%
Other values (13) 11399
 
0.1%

Most frequent character per category

Other Symbol
ValueCountFrequency (%)
🔥 15405
18.1%
11818
 
13.9%
4752
 
5.6%
4437
 
5.2%
🤩 4110
 
4.8%
2874
 
3.4%
2362
 
2.8%
🚀 2314
 
2.7%
🔞 2183
 
2.6%
📽 2134
 
2.5%
Other values (646) 32818
38.5%
Lowercase Letter
ValueCountFrequency (%)
e 951284
13.3%
o 617337
 
8.6%
i 606223
 
8.5%
r 604599
 
8.4%
s 600581
 
8.4%
a 512714
 
7.2%
n 499289
 
7.0%
t 436832
 
6.1%
l 383455
 
5.3%
u 278335
 
3.9%
Other values (426) 1677456
23.4%
Other Letter
ValueCountFrequency (%)
1243
43.4%
143
 
5.0%
103
 
3.6%
103
 
3.6%
ا 94
 
3.3%
75
 
2.6%
ر 46
 
1.6%
𓂀 35
 
1.2%
ن 33
 
1.2%
ي 33
 
1.2%
Other values (293) 956
33.4%
Uppercase Letter
ValueCountFrequency (%)
T 249121
13.7%
B 189526
 
10.4%
N 155423
 
8.5%
I 114118
 
6.3%
C 109033
 
6.0%
S 99600
 
5.5%
A 99120
 
5.4%
M 90357
 
5.0%
F 82935
 
4.6%
P 74428
 
4.1%
Other values (216) 558113
30.6%
Modifier Letter
ValueCountFrequency (%)
32
17.3%
29
15.7%
ˏ 11
 
5.9%
ˊ 11
 
5.9%
ˎ 11
 
5.9%
ˋ 11
 
5.9%
ʸ 8
 
4.3%
8
 
4.3%
5
 
2.7%
ˡ 5
 
2.7%
Other values (31) 54
29.2%
Other Punctuation
ValueCountFrequency (%)
. 27547
46.8%
& 10921
 
18.5%
# 7889
 
13.4%
' 4041
 
6.9%
@ 2121
 
3.6%
* 1706
 
2.9%
, 1319
 
2.2%
! 1308
 
2.2%
: 580
 
1.0%
/ 536
 
0.9%
Other values (19) 944
 
1.6%
Nonspacing Mark
ValueCountFrequency (%)
10961
95.6%
ً 266
 
2.3%
َ 106
 
0.9%
57
 
0.5%
26
 
0.2%
14
 
0.1%
4
 
< 0.1%
4
 
< 0.1%
͡ 4
 
< 0.1%
4
 
< 0.1%
Other values (16) 21
 
0.2%
Format
ValueCountFrequency (%)
267
40.3%
177
26.7%
68
 
10.3%
󠁧 28
 
4.2%
󠁢 24
 
3.6%
󠁿 24
 
3.6%
󠁳 20
 
3.0%
󠁣 12
 
1.8%
󠁴 12
 
1.8%
󠁷 8
 
1.2%
Other values (7) 23
 
3.5%
Decimal Number
ValueCountFrequency (%)
9 7048
36.6%
1 4902
25.5%
5 1991
 
10.3%
0 1809
 
9.4%
7 1116
 
5.8%
2 641
 
3.3%
6 444
 
2.3%
𝟤 416
 
2.2%
8 306
 
1.6%
3 300
 
1.6%
Other values (5) 279
 
1.4%
Math Symbol
ValueCountFrequency (%)
+ 2223
87.7%
| 155
 
6.1%
~ 74
 
2.9%
= 45
 
1.8%
21
 
0.8%
4
 
0.2%
4
 
0.2%
2
 
0.1%
2
 
0.1%
2
 
0.1%
Other values (3) 3
 
0.1%
Currency Symbol
ValueCountFrequency (%)
895
61.3%
¢ 282
 
19.3%
$ 184
 
12.6%
฿ 89
 
6.1%
3
 
0.2%
2
 
0.1%
1
 
0.1%
1
 
0.1%
1
 
0.1%
1
 
0.1%
Other values (2) 2
 
0.1%
Modifier Symbol
ValueCountFrequency (%)
🏻 81
35.5%
🏼 60
26.3%
🏽 27
 
11.8%
˗ 22
 
9.6%
🏾 14
 
6.1%
🏿 9
 
3.9%
` 6
 
2.6%
^ 3
 
1.3%
¨ 2
 
0.9%
¯ 2
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 2323
78.7%
[ 617
 
20.9%
{ 4
 
0.1%
3
 
0.1%
2
 
0.1%
2
 
0.1%
1
 
< 0.1%
1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 2355
79.0%
] 617
 
20.7%
} 4
 
0.1%
3
 
0.1%
1
 
< 0.1%
1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 5151
98.7%
62
 
1.2%
4
 
0.1%
3
 
0.1%
1
 
< 0.1%
Spacing Mark
ValueCountFrequency (%)
8
61.5%
ि 2
 
15.4%
2
 
15.4%
1
 
7.7%
Final Punctuation
ValueCountFrequency (%)
433
96.7%
13
 
2.9%
» 2
 
0.4%
Initial Punctuation
ValueCountFrequency (%)
22
81.5%
3
 
11.1%
« 2
 
7.4%
Other Number
ValueCountFrequency (%)
² 3
60.0%
¹ 1
 
20.0%
1
 
20.0%
Space Separator
ValueCountFrequency (%)
804352
> 99.9%
  71
 
< 0.1%
Private Use
ValueCountFrequency (%)
10
66.7%
5
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 8458
100.0%
Enclosing Mark
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8971753
89.7%
Common 1006918
 
10.1%
Inherited 11700
 
0.1%
Cyrillic 1631
 
< 0.1%
Devanagari 1305
 
< 0.1%
Georgian 1199
 
< 0.1%
Greek 876
 
< 0.1%
Han 681
 
< 0.1%
Arabic 428
 
< 0.1%
Hangul 218
 
< 0.1%
Other values (15) 490
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
804352
79.9%
. 27547
 
2.7%
🔥 15405
 
1.5%
11818
 
1.2%
& 10921
 
1.1%
_ 8458
 
0.8%
# 7889
 
0.8%
9 7048
 
0.7%
- 5151
 
0.5%
1 4902
 
0.5%
Other values (1110) 103427
 
10.3%
Latin
ValueCountFrequency (%)
e 951284
 
10.6%
o 617337
 
6.9%
i 606223
 
6.8%
r 604599
 
6.7%
s 600581
 
6.7%
a 512714
 
5.7%
n 499289
 
5.6%
t 436832
 
4.9%
l 383455
 
4.3%
u 278335
 
3.1%
Other values (237) 3481104
38.8%
Han
ValueCountFrequency (%)
103
 
15.1%
103
 
15.1%
75
 
11.0%
28
 
4.1%
28
 
4.1%
28
 
4.1%
14
 
2.1%
10
 
1.5%
9
 
1.3%
8
 
1.2%
Other values (110) 275
40.4%
Cyrillic
ValueCountFrequency (%)
ѕ 394
24.2%
є 378
23.2%
и 176
10.8%
я 172
10.5%
у 146
 
9.0%
т 83
 
5.1%
н 26
 
1.6%
а 23
 
1.4%
ҽ 21
 
1.3%
С 15
 
0.9%
Other values (41) 197
12.1%
Greek
ValueCountFrequency (%)
α 227
25.9%
σ 201
22.9%
ι 190
21.7%
ρ 81
 
9.2%
υ 36
 
4.1%
ο 11
 
1.3%
ν 11
 
1.3%
Σ 9
 
1.0%
ω 8
 
0.9%
Λ 8
 
0.9%
Other values (32) 94
10.7%
Hangul
ValueCountFrequency (%)
143
65.6%
10
 
4.6%
6
 
2.8%
5
 
2.3%
4
 
1.8%
4
 
1.8%
4
 
1.8%
3
 
1.4%
3
 
1.4%
3
 
1.4%
Other values (25) 33
 
15.1%
Arabic
ValueCountFrequency (%)
ا 94
22.0%
ر 46
10.7%
ن 33
 
7.7%
ي 33
 
7.7%
م 31
 
7.2%
ل 30
 
7.0%
ع 23
 
5.4%
ف 23
 
5.4%
س 21
 
4.9%
ب 18
 
4.2%
Other values (22) 76
17.8%
Katakana
ValueCountFrequency (%)
11
21.2%
9
17.3%
3
 
5.8%
2
 
3.8%
2
 
3.8%
2
 
3.8%
2
 
3.8%
2
 
3.8%
1
 
1.9%
1
 
1.9%
Other values (17) 17
32.7%
Devanagari
ValueCountFrequency (%)
1243
95.2%
8
 
0.6%
8
 
0.6%
4
 
0.3%
4
 
0.3%
4
 
0.3%
4
 
0.3%
2
 
0.2%
2
 
0.2%
2
 
0.2%
Other values (12) 24
 
1.8%
Thai
ValueCountFrequency (%)
4
 
12.1%
4
 
12.1%
4
 
12.1%
3
 
9.1%
2
 
6.1%
2
 
6.1%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
Other values (10) 10
30.3%
Hiragana
ValueCountFrequency (%)
7
15.6%
6
13.3%
6
13.3%
6
13.3%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
Other values (8) 8
17.8%
Hebrew
ValueCountFrequency (%)
ן 5
20.8%
ס 2
 
8.3%
ם 2
 
8.3%
ה 2
 
8.3%
א 1
 
4.2%
ח 1
 
4.2%
ת 1
 
4.2%
ד 1
 
4.2%
ע 1
 
4.2%
מ 1
 
4.2%
Other values (7) 7
29.2%
Canadian_Aboriginal
ValueCountFrequency (%)
12
18.2%
12
18.2%
9
13.6%
7
10.6%
4
 
6.1%
3
 
4.5%
3
 
4.5%
3
 
4.5%
3
 
4.5%
2
 
3.0%
Other values (6) 8
12.1%
Inherited
ValueCountFrequency (%)
10961
93.7%
267
 
2.3%
ً 266
 
2.3%
َ 106
 
0.9%
68
 
0.6%
14
 
0.1%
͡ 4
 
< 0.1%
4
 
< 0.1%
͜ 2
 
< 0.1%
̮ 2
 
< 0.1%
Other values (5) 6
 
0.1%
Khmer
ValueCountFrequency (%)
2
15.4%
2
15.4%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
Armenian
ValueCountFrequency (%)
Ե 39
39.8%
օ 18
18.4%
վ 13
 
13.3%
ղ 11
 
11.2%
մ 6
 
6.1%
Թ 4
 
4.1%
հ 4
 
4.1%
ց 1
 
1.0%
ռ 1
 
1.0%
ֆ 1
 
1.0%
Cherokee
ValueCountFrequency (%)
6
54.5%
2
 
18.2%
1
 
9.1%
1
 
9.1%
1
 
9.1%
Georgian
ValueCountFrequency (%)
1192
99.4%
4
 
0.3%
2
 
0.2%
1
 
0.1%
Tibetan
ValueCountFrequency (%)
57
90.5%
3
 
4.8%
3
 
4.8%
Unknown
ValueCountFrequency (%)
10
66.7%
5
33.3%
Gujarati
ValueCountFrequency (%)
6
85.7%
1
 
14.3%
Egyptian_Hieroglyphs
ValueCountFrequency (%)
𓂀 35
100.0%
Lao
ValueCountFrequency (%)
26
100.0%
Tifinagh
ValueCountFrequency (%)
1
100.0%
Bopomofo
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9870911
98.7%
None 55352
 
0.6%
Dingbats 19989
 
0.2%
Math Alphanum 14669
 
0.1%
VS 10975
 
0.1%
Misc Symbols 10344
 
0.1%
Letterlike Symbols 2555
 
< 0.1%
Enclosed Alphanum Sup 1956
 
< 0.1%
Cyrillic 1625
 
< 0.1%
Devanagari 1305
 
< 0.1%
Other values (43) 7518
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 951284
 
9.6%
804352
 
8.1%
o 617337
 
6.3%
i 606223
 
6.1%
r 604599
 
6.1%
s 600581
 
6.1%
a 512714
 
5.2%
n 499289
 
5.1%
t 436832
 
4.4%
l 383455
 
3.9%
Other values (83) 3854245
39.0%
None
ValueCountFrequency (%)
🔥 15405
27.8%
🤩 4110
 
7.4%
🚀 2314
 
4.2%
🔞 2183
 
3.9%
📽 2134
 
3.9%
® 2071
 
3.7%
ë 1590
 
2.9%
📈 1584
 
2.9%
📭 1230
 
2.2%
🗺 1146
 
2.1%
Other values (621) 21585
39.0%
Dingbats
ValueCountFrequency (%)
11818
59.1%
4437
 
22.2%
2874
 
14.4%
239
 
1.2%
174
 
0.9%
91
 
0.5%
75
 
0.4%
32
 
0.2%
26
 
0.1%
26
 
0.1%
Other values (30) 197
 
1.0%
VS
ValueCountFrequency (%)
10961
99.9%
14
 
0.1%
Misc Symbols
ValueCountFrequency (%)
4752
45.9%
2087
20.2%
984
 
9.5%
453
 
4.4%
382
 
3.7%
248
 
2.4%
237
 
2.3%
208
 
2.0%
95
 
0.9%
91
 
0.9%
Other values (67) 807
 
7.8%
Letterlike Symbols
ValueCountFrequency (%)
2362
92.4%
159
 
6.2%
12
 
0.5%
8
 
0.3%
4
 
0.2%
2
 
0.1%
2
 
0.1%
1
 
< 0.1%
1
 
< 0.1%
1
 
< 0.1%
Other values (3) 3
 
0.1%
Devanagari
ValueCountFrequency (%)
1243
95.2%
8
 
0.6%
8
 
0.6%
4
 
0.3%
4
 
0.3%
4
 
0.3%
4
 
0.3%
2
 
0.2%
2
 
0.2%
2
 
0.2%
Other values (12) 24
 
1.8%
Georgian
ValueCountFrequency (%)
1192
99.4%
4
 
0.3%
2
 
0.2%
1
 
0.1%
Math Alphanum
ValueCountFrequency (%)
𝚎 992
 
6.8%
𝖾 833
 
5.7%
𝗌 832
 
5.7%
𝚕 489
 
3.3%
𝗋 417
 
2.8%
𝗅 417
 
2.8%
𝗈 417
 
2.8%
𝖢 417
 
2.8%
𝗏 416
 
2.8%
𝟤 416
 
2.8%
Other values (318) 9023
61.5%
Currency Symbols
ValueCountFrequency (%)
895
98.8%
3
 
0.3%
2
 
0.2%
1
 
0.1%
1
 
0.1%
1
 
0.1%
1
 
0.1%
1
 
0.1%
1
 
0.1%
Punctuation
ValueCountFrequency (%)
433
39.8%
267
24.5%
177
16.3%
84
 
7.7%
68
 
6.2%
22
 
2.0%
13
 
1.2%
4
 
0.4%
4
 
0.4%
4
 
0.4%
Other values (8) 13
 
1.2%
Cyrillic
ValueCountFrequency (%)
ѕ 394
24.2%
є 378
23.3%
и 176
10.8%
я 172
10.6%
у 146
 
9.0%
т 83
 
5.1%
н 26
 
1.6%
а 23
 
1.4%
ҽ 21
 
1.3%
С 15
 
0.9%
Other values (36) 191
11.8%
Enclosed Alphanum Sup
ValueCountFrequency (%)
🇺 291
14.9%
🇵 223
11.4%
🇷 177
9.0%
🇪 169
8.6%
🇸 163
 
8.3%
🇦 133
 
6.8%
🇧 119
 
6.1%
🇨 109
 
5.6%
🇬 101
 
5.2%
🇮 63
 
3.2%
Other values (29) 408
20.9%
Arabic
ValueCountFrequency (%)
ً 266
33.2%
َ 106
 
13.2%
ا 94
 
11.7%
ر 46
 
5.7%
ن 33
 
4.1%
ي 33
 
4.1%
م 31
 
3.9%
ل 30
 
3.7%
ع 23
 
2.9%
ف 23
 
2.9%
Other values (26) 117
14.6%
Compat Jamo
ValueCountFrequency (%)
143
87.7%
10
 
6.1%
6
 
3.7%
4
 
2.5%
Emoticons
ValueCountFrequency (%)
😎 135
25.6%
😷 127
24.1%
😈 47
 
8.9%
😘 31
 
5.9%
😁 25
 
4.7%
😃 20
 
3.8%
😻 19
 
3.6%
😮 13
 
2.5%
😊 12
 
2.3%
🙋 12
 
2.3%
Other values (21) 86
16.3%
Phonetic Ext
ValueCountFrequency (%)
120
22.6%
77
14.5%
62
11.7%
35
 
6.6%
32
 
6.0%
29
 
5.5%
28
 
5.3%
22
 
4.1%
22
 
4.1%
19
 
3.6%
Other values (28) 85
16.0%
Specials
ValueCountFrequency (%)
104
100.0%
CJK
ValueCountFrequency (%)
103
 
15.8%
103
 
15.8%
75
 
11.5%
28
 
4.3%
28
 
4.3%
14
 
2.1%
10
 
1.5%
9
 
1.4%
8
 
1.2%
8
 
1.2%
Other values (109) 267
40.9%
IPA Ext
ValueCountFrequency (%)
ɴ 92
19.7%
ɪ 54
11.6%
ɢ 48
10.3%
ɛ 42
9.0%
ɑ 39
8.4%
ʏ 37
7.9%
ʀ 32
 
6.9%
ɾ 25
 
5.4%
ʜ 18
 
3.9%
ʟ 17
 
3.6%
Other values (19) 62
13.3%
Thai
ValueCountFrequency (%)
฿ 89
73.0%
4
 
3.3%
4
 
3.3%
4
 
3.3%
3
 
2.5%
2
 
1.6%
2
 
1.6%
1
 
0.8%
1
 
0.8%
1
 
0.8%
Other values (11) 11
 
9.0%
Tibetan
ValueCountFrequency (%)
57
90.5%
3
 
4.8%
3
 
4.8%
Armenian
ValueCountFrequency (%)
Ե 39
39.8%
օ 18
18.4%
վ 13
 
13.3%
ղ 11
 
11.2%
մ 6
 
6.1%
Թ 4
 
4.1%
հ 4
 
4.1%
ց 1
 
1.0%
ռ 1
 
1.0%
ֆ 1
 
1.0%
Egyptian Hieroglyphs
ValueCountFrequency (%)
𓂀 35
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
34
65.4%
2
 
3.8%
2
 
3.8%
2
 
3.8%
2
 
3.8%
2
 
3.8%
1
 
1.9%
1
 
1.9%
1
 
1.9%
1
 
1.9%
Other values (4) 4
 
7.7%
CJK Ext A
ValueCountFrequency (%)
28
100.0%
Tags
ValueCountFrequency (%)
󠁧 28
19.4%
󠁢 24
16.7%
󠁿 24
16.7%
󠁳 20
13.9%
󠁣 12
8.3%
󠁴 12
8.3%
󠁷 8
 
5.6%
󠁬 8
 
5.6%
󠁥 4
 
2.8%
󠁮 4
 
2.8%
Lao
ValueCountFrequency (%)
26
100.0%
Modifier Letters
ValueCountFrequency (%)
˗ 22
25.6%
ˏ 11
12.8%
ˊ 11
12.8%
ˎ 11
12.8%
ˋ 11
12.8%
ʸ 8
 
9.3%
ˡ 5
 
5.8%
ʰ 2
 
2.3%
˵ 2
 
2.3%
ˢ 1
 
1.2%
Other values (2) 2
 
2.3%
Math Operators
ValueCountFrequency (%)
21
77.8%
2
 
7.4%
2
 
7.4%
1
 
3.7%
1
 
3.7%
Katakana
ValueCountFrequency (%)
16
24.2%
11
16.7%
9
13.6%
3
 
4.5%
2
 
3.0%
2
 
3.0%
2
 
3.0%
2
 
3.0%
2
 
3.0%
1
 
1.5%
Other values (16) 16
24.2%
Geometric Shapes
ValueCountFrequency (%)
16
66.7%
2
 
8.3%
2
 
8.3%
2
 
8.3%
1
 
4.2%
1
 
4.2%
Misc Technical
ValueCountFrequency (%)
15
88.2%
1
 
5.9%
1
 
5.9%
UCAS
ValueCountFrequency (%)
12
18.2%
12
18.2%
9
13.6%
7
10.6%
4
 
6.1%
3
 
4.5%
3
 
4.5%
3
 
4.5%
3
 
4.5%
2
 
3.0%
Other values (6) 8
12.1%
PUA
ValueCountFrequency (%)
10
66.7%
5
33.3%
Hiragana
ValueCountFrequency (%)
7
15.6%
6
13.3%
6
13.3%
6
13.3%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
Other values (8) 8
17.8%
Gujarati
ValueCountFrequency (%)
6
85.7%
1
 
14.3%
Cherokee
ValueCountFrequency (%)
6
54.5%
2
 
18.2%
1
 
9.1%
1
 
9.1%
1
 
9.1%
Latin Ext Additional
ValueCountFrequency (%)
5
71.4%
1
 
14.3%
1
 
14.3%
Greek Ext
ValueCountFrequency (%)
5
100.0%
Hebrew
ValueCountFrequency (%)
ן 5
20.8%
ס 2
 
8.3%
ם 2
 
8.3%
ה 2
 
8.3%
א 1
 
4.2%
ח 1
 
4.2%
ת 1
 
4.2%
ד 1
 
4.2%
ע 1
 
4.2%
מ 1
 
4.2%
Other values (7) 7
29.2%
Hangul
ValueCountFrequency (%)
5
 
9.3%
4
 
7.4%
4
 
7.4%
3
 
5.6%
3
 
5.6%
3
 
5.6%
3
 
5.6%
3
 
5.6%
2
 
3.7%
2
 
3.7%
Other values (20) 22
40.7%
Diacriticals
ValueCountFrequency (%)
͡ 4
40.0%
͜ 2
20.0%
̮ 2
20.0%
̷ 1
 
10.0%
́ 1
 
10.0%
Diacriticals Sup
ValueCountFrequency (%)
4
100.0%
Khmer
ValueCountFrequency (%)
2
15.4%
2
15.4%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
Enclosed Ideographic Sup
ValueCountFrequency (%)
🈴 2
14.3%
🈸 2
14.3%
🈷 2
14.3%
🈯 2
14.3%
🈶 2
14.3%
🈳 2
14.3%
🈹 2
14.3%
Phonetic Ext Sup
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
CJK Compat Forms
ValueCountFrequency (%)
2
100.0%
Cyrillic Sup
ValueCountFrequency (%)
ԋ 2
50.0%
ԃ 1
25.0%
Ԁ 1
25.0%
Jamo
ValueCountFrequency (%)
1
100.0%
Tifinagh
ValueCountFrequency (%)
1
100.0%
Bopomofo
ValueCountFrequency (%)
1
100.0%
Block Elements
ValueCountFrequency (%)
1
50.0%
1
50.0%

videoUrl
URL

Missing 

Distinct77506
Distinct (%)55.2%
Missing645425
Missing (%)82.1%
Memory size38.9 MiB
https://video.twimg.com/amplify_video/1098673630966358016/vid/640x360/s-QArpal8Y5g-1Co.mp4?tag=9
 
127
https://video.twimg.com/amplify_video/1126626046558625792/pl/JEInfD21OO9wxmag.m3u8?tag=12
 
126
https://video.twimg.com/ext_tw_video/1108764347713703937/pu/vid/320x180/zRBXk6lGOg0MhciE.mp4?tag=8
 
110
https://video.twimg.com/amplify_video/1092622594489139203/vid/320x180/7qZRbTf5BH1k7kjF.mp4?tag=9
 
103
https://video.twimg.com/amplify_video/1100527279334219776/vid/320x180/nSst4z6uKgBVp9M2.mp4?tag=9
 
100
Other values (77501)
139925 
(Missing)
645425 
ValueCountFrequency (%)
https://video.twimg.com/amplify_video/1098673630966358016/vid/640x360/s-QArpal8Y5g-1Co.mp4?tag=9 127
 
< 0.1%
https://video.twimg.com/amplify_video/1126626046558625792/pl/JEInfD21OO9wxmag.m3u8?tag=12 126
 
< 0.1%
https://video.twimg.com/ext_tw_video/1108764347713703937/pu/vid/320x180/zRBXk6lGOg0MhciE.mp4?tag=8 110
 
< 0.1%
https://video.twimg.com/amplify_video/1092622594489139203/vid/320x180/7qZRbTf5BH1k7kjF.mp4?tag=9 103
 
< 0.1%
https://video.twimg.com/amplify_video/1100527279334219776/vid/320x180/nSst4z6uKgBVp9M2.mp4?tag=9 100
 
< 0.1%
https://video.twimg.com/ext_tw_video/1111845697232355329/pu/pl/M1dSwPCbKpjCJyOB.m3u8?tag=8 99
 
< 0.1%
https://video.twimg.com/amplify_video/1104512132241113088/pl/8HfdRDRy6jgn4AxA.m3u8?tag=11 78
 
< 0.1%
https://video.twimg.com/amplify_video/1104509561636048897/pl/Zsll6fXKKJ-m7kQD.m3u8?tag=11 78
 
< 0.1%
https://video.twimg.com/amplify_video/1104508068052774912/vid/432x180/I5aWgI_WJVeb93w7.mp4?tag=11 77
 
< 0.1%
https://video.twimg.com/ext_tw_video/1098670036225536000/pu/vid/360x640/8KDXU-GAsAa5_mRb.mp4?tag=6 76
 
< 0.1%
Other values (77496) 139517
 
17.8%
(Missing) 645425
82.1%
ValueCountFrequency (%)
https 140491
 
17.9%
(Missing) 645425
82.1%
ValueCountFrequency (%)
video.twimg.com 140491
 
17.9%
(Missing) 645425
82.1%
ValueCountFrequency (%)
/amplify_video/1098673630966358016/vid/640x360/s-QArpal8Y5g-1Co.mp4 127
 
< 0.1%
/amplify_video/1126626046558625792/pl/JEInfD21OO9wxmag.m3u8 126
 
< 0.1%
/ext_tw_video/1108764347713703937/pu/vid/320x180/zRBXk6lGOg0MhciE.mp4 110
 
< 0.1%
/amplify_video/1092622594489139203/vid/320x180/7qZRbTf5BH1k7kjF.mp4 103
 
< 0.1%
/amplify_video/1100527279334219776/vid/320x180/nSst4z6uKgBVp9M2.mp4 100
 
< 0.1%
/ext_tw_video/1111845697232355329/pu/pl/M1dSwPCbKpjCJyOB.m3u8 99
 
< 0.1%
/amplify_video/1104509561636048897/pl/Zsll6fXKKJ-m7kQD.m3u8 78
 
< 0.1%
/amplify_video/1104512132241113088/pl/8HfdRDRy6jgn4AxA.m3u8 78
 
< 0.1%
/amplify_video/1104508068052774912/vid/432x180/I5aWgI_WJVeb93w7.mp4 77
 
< 0.1%
/ext_tw_video/1098670036225536000/pu/vid/360x640/8KDXU-GAsAa5_mRb.mp4 76
 
< 0.1%
Other values (77496) 139517
 
17.8%
(Missing) 645425
82.1%
ValueCountFrequency (%)
tag=9 26957
 
3.4%
tag=6 20364
 
2.6%
tag=8 19238
 
2.4%
tag=13 17994
 
2.3%
15412
 
2.0%
tag=11 15114
 
1.9%
tag=10 12847
 
1.6%
tag=12 6854
 
0.9%
tag=2 1994
 
0.3%
tag=5 1728
 
0.2%
Other values (4) 1989
 
0.3%
(Missing) 645425
82.1%
ValueCountFrequency (%)
140491
 
17.9%
(Missing) 645425
82.1%

Interactions

2025-03-14T23:37:01.674718image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:56.570709image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:57.286190image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:57.981210image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:58.674377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:59.386795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:00.143018image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:00.905438image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:01.770868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:56.664600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:57.372421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:58.072117image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:58.762906image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:59.477201image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:00.236927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:01.002782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:01.871308image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:56.753492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:57.457027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:58.155097image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:58.850979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:59.569757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:00.333766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:01.098144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:01.967462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:56.841043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:57.541895image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:58.239965image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:58.935576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:59.665241image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:00.433936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:01.194279image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:02.069658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:56.931472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:57.628725image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:58.325527image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:59.026506image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:59.756548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:00.527990image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:01.291223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:02.180481image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:57.020889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:57.719705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:58.413070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:59.117537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:59.850352image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:00.622344image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:01.391755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:02.276810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:57.111718image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:57.805836image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:58.500048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:59.206804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:59.946093image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:00.713772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:01.485927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:02.369904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:57.199212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:57.893620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:58.584908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:36:59.295765image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:00.044512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:00.809170image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-14T23:37:01.577583image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-03-14T23:37:08.379635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
edInputeditorengagesisApprovedisRTlikesretweetsrtUsIDtopicNametweetIDusFlwrsusID
edInput1.0000.5780.0030.9640.1660.0030.0030.0690.2580.0260.0830.069
editor0.5781.0000.1680.6220.0150.1800.122-0.0220.2070.439-0.1130.100
engages0.0030.1681.0000.0030.0290.9940.9560.1480.022-0.0020.1360.152
isApproved0.9640.6220.0031.0000.1080.0040.0030.0960.3560.0360.0850.072
isRT0.1660.0150.0290.1081.0000.0290.0210.5080.3950.1300.1590.347
likes0.0030.1800.9940.0040.0291.0000.9210.1500.0230.0070.1120.165
retweets0.0030.1220.9560.0030.0210.9211.0000.1290.011-0.0310.1990.099
rtUsID0.069-0.0220.1480.0960.5080.1500.1291.0000.376-0.101-0.5110.388
topicName0.2580.2070.0220.3560.3950.0230.0110.3761.0000.0450.2680.303
tweetID0.0260.439-0.0020.0360.1300.007-0.031-0.1010.0451.0000.072-0.117
usFlwrs0.083-0.1130.1360.0850.1590.1120.199-0.5110.2680.0721.000-0.721
usID0.0690.1000.1520.0720.3470.1650.0990.3880.303-0.117-0.7211.000

Missing values

2025-03-14T23:37:02.576271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-14T23:37:03.131892image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-03-14T23:37:04.373014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

tweetIDcrDateedInputeditorengagesisApprovedisEdNeedisRTlikesphotoUrlretweetsrtUsIDtexttopicNameusFlwrsusIDusNamevideoUrl
010708674712451645442018-12-07 02:27:55-1-198FalseTrueFalse64https://pbs.twimg.com/media/Dtx8SiIWkAImVsb.jpg34-1The immediate impulse for an alliance of the EU's northern states is Brexit https://t.co/nlhUD36hay https://t.co/shwMWpjjuKBusiness234645325988062The EconomistNaN
110708680178888376332018-12-07 02:30:05-1-113FalseTrueFalse10https://pbs.twimg.com/media/Dtx8yTyW4AEciqP.jpg3-1America's economy is flashing some warning signs, but -- for now -- the labor market appears to be going strong https://t.co/xvCPgtqMzy https://t.co/0sQdzAsME3Business173280916184358CNN BusinessNaN
210708680128640286732018-12-07 02:30:04-1-112FalseTrueFalse8NaN4-1Lyft files for what is expected to be one of the hottest IPOs in 2019 https://t.co/qEjyniazlDBusiness225398925053299FORTUNENaN
310708679952395550752018-12-07 02:30:00-1-15FalseTrueFalse4NaN1-1Exporters still waiting to get Rs 6,000 crore worth of input tax credit refunds\n\nMany being denied tax refunds by state governments, such as Andhra Pradesh, Uttar Pradesh, Bihar and Chhattisgarh, who say they are cash starved\n\n@Subhayan_ism @GST_Council\n\nhttps://t.co/QRBg8b98RrBusiness170405643855487Business StandardNaN
410708679952058859522018-12-07 02:30:00-1-15FalseTrueFalse2NaN3-1Ride-hailing firm Lyft races to leave Uber behind in IPO chase https://t.co/0qCsdx2LYS https://t.co/gHZLUntYkLBusiness199766215110357Reuters Businesshttps://video.twimg.com/amplify_video/1070811671948681226/vid/320x180/5hE60WR-z0Q537YU.mp4?tag=9
510708680196000768022018-12-07 02:30:06-1-11116FalseTrueFalse793NaN323-1Jaguar hugs! https://t.co/l1ICUSyjp7Animal68526942754965528895488I_love_naturehttps://video.twimg.com/ext_tw_video/1070363423303622656/pu/pl/i8Yo-hLiaVvItD_9.m3u8?tag=6
610708681021607690252018-12-07 02:30:25-1-131FalseTrueFalse17https://pbs.twimg.com/media/Dtx83JvX4AE48aw.jpg14-1-Asian stocks post modest gains \n-S&P 500 futures little changed\n-10-year Treasury yields stayed near 2.90%\n-Oil continues to be a drag on sentiment\n-Next up for embattled traders: the monthly U.S. payrolls report\nhttps://t.co/8cwVkXpoWQ https://t.co/EBp6jNaJP3Business503322134713362BloombergNaN
710708680718443765762018-12-07 02:30:18-1-19FalseTrueFalse7NaN2-1What's your pick? https://t.co/a0nnFRqIQ3Business23180882735591Fast CompanyNaN
810708680633592627202018-12-07 02:30:16-1-14FalseTrueFalse4NaN0-1Dick's CEO Ed Stack totals up how many employees quit over assault-style weapon decision https://t.co/kgOa4CQ5NRBusiness4873614921083Business JournalsNaN
910708680258873876482018-12-07 02:30:07-1-190FalseTrueFalse63NaN27-1A meeting of tech leaders at the White House marked an easing of tensions between Washington and Silicon Valley https://t.co/blFfALEgILBusiness161985223108351The Wall Street JournalNaN
tweetIDcrDateedInputeditorengagesisApprovedisEdNeedisRTlikesphotoUrlretweetsrtUsIDtexttopicNameusFlwrsusIDusNamevideoUrl
78590611530930296175329282019-07-22 00:02:56-1-1711FalseTrueTrue544NaN167865670110593155072like and retweet this if you think it's a vibe!!! 🔥✈️✈️✈️ https://t.co/A9J0MCtvDIAnimal1451100521587147591680icecreampathttps://video.twimg.com/ext_tw_video/1153090666596978688/pu/pl/Fxm1w0_pmSchNwsU.m3u8?tag=10
78590711539862324073472012019-07-24 11:12:12-1-11560FalseTrueTrue893https://pbs.twimg.com/media/D_Rm_h7VAAEyEe5.jpg6672271543909P O S I T I V I T Y https://t.co/oPo4j8bvh8Funny164127768030487646396416My FeelingNaN
78590811540788972201000972019-07-24 17:20:25-1-1864FalseTrueTrue523https://pbs.twimg.com/media/D90uCeWUcAAapsN.jpg3412271543909G O O D V I B E S O N L Y https://t.co/39nIzxdOz3Funny164127768030487646396416My FeelingNaN
78590911537384046365736962019-07-23 18:47:25-1-1229FalseTrueTrue191NaN38781427301472874497Skull Basher Axe 👀\n\nLike if you want this piece \n\nOn Sale: https://t.co/01QF855say https://t.co/byC3NKoPopInteresting45615778150181468512256Blade Cityhttps://video.twimg.com/ext_tw_video/1153738015581331462/pu/vid/320x320/p2UV3CxapFMGWmdb.mp4?tag=10
78591011352774758173040652019-06-02 20:10:17-1-11464FalseTrueTrue1303NaN1612355808260The best part of David Lynch's "Eraserhead Stories" is when he talks about buying a supermarket Dutch apple pie for the same price as a single slice at the Hamburger Hamlet and then subsequently sneaking his own slices into the Hamburger Hamlet, describing it as "a real thrill."Photography39896421542096Ari AsterNaN
78591111473258516141178882019-07-06 02:06:13-1-13FalseTrueTrue1NaN2542154137Relations are DIFFERENT\nnot DIFFICULT.Motivational85625542154137Wit & Wisdom 💯NaN
78591211531840587146240012019-07-22 06:04:39-1-1867FalseTrueTrue561https://pbs.twimg.com/media/EADuxohU8AAQo8G.jpg306858516111410647040"to live a creative life, we must lose our fear of being wrong"......... https://t.co/LF0e0xV5Q7Interesting2084172920686840DeepFeling™NaN
78591311530488021162926082019-07-21 21:07:11-1-14605FalseTrueTrue4253NaN3523282859598Who's your comic crush? https://t.co/H29dhXw3kfMemes7024207436266454Twitter Movieshttps://video.twimg.com/amplify_video/1153047495326355457/vid/1280x720/P996nFjt3ncUO467.mp4?tag=13
78591411540630529978368012019-07-24 16:17:27-1-15638TrueTrueFalse4996https://pbs.twimg.com/media/EAQOObJWwAASaxj.jpg642-1After a flight of 195 hours, 18 minutes, 35 seconds - the #Apollo11 crew splashed down in the North Pacific Ocean, 900 miles southwest of Hawaii! Here’s a photo of their recovery as we celebrate the #Apollo50th anniversary: https://t.co/Y4zhGTQlPj https://t.co/fBpvcECsjpRandom3203079711348282NASANaN
78591510737230277186887682018-12-14 23:34:53-1-14181FalseTrueTrue3282https://pbs.twimg.com/media/DuahZZeUYAA7-55.jpg8992355808260Scarface's Action Figure Tony Montana cutting open a pack of Flour on a kitchen table\n(by artist VSE OK) https://t.co/vOqvOh7EFnPhotography606924235580826041 StrangeNaN